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            <article class="content wrap" id="_content" data-uid="TensorFlow.TFShape">
  
  
  <h1 id="TensorFlow_TFShape" data-uid="TensorFlow.TFShape">Class TFShape
  </h1>
  <div class="markdown level0 summary"><p>Represents the shape of a tensor, it describes how many dimensions the tensor has in a given axis</p>
</div>
  <div class="markdown level0 conceptual"></div>
  <div class="inheritance">
    <h5>Inheritance</h5>
    <div class="level0"><span class="xref">System.Object</span></div>
    <div class="level1"><span class="xref">TFShape</span></div>
  </div>
  <h6><strong>Namespace</strong>: <a class="xref" href="../TensorFlow.html">TensorFlow</a></h6>
  <h6><strong>Assembly</strong>: TensorFlowSharp.dll</h6>
  <h5 id="TensorFlow_TFShape_syntax">Syntax</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public class TFShape</code></pre>
  </div>
  <h5 id="TensorFlow_TFShape_remarks"><strong>Remarks</strong></h5>
  <div class="markdown level0 remarks"><p>
            The shapes can be created by calling the constructor with the number of dimensions
            in the shape.   The null value is used to specify that the shape is unknown,
            an empty array is used to create a scalar, and other values are used to specify
            the number of dimensions.
            </p>
    <p>
            For the Unknown case, you can use <span class="xref">TensorFlor.TFShape.Unknown</span>, for
            scalars, you can use the <span class="xref">TensorFlor.TFShape.Scalar</span> shape.
            </p>
    <p>
            To create a 2-element vector, use:
            new TFShape (2)
            </p>
    <p>
            To create a 2x3 matrix, use:
            new TFShape (2, 3)
            </p>
    <p>
            To create a shape with an unknown number of elements, you can pass the value
            -1.  This is typically used to indicate the shape of tensors that represent a
            variable-sized batch of values.
            </p>
    <p>
            To create a matrix with 4 columns and an unknown number of rows:
            var batch = new TFShape (-1, 4)
            </p></div>
  <h3 id="constructors">Constructors
  </h3>
  
  
  <a id="TensorFlow_TFShape__ctor_" data-uid="TensorFlow.TFShape.#ctor*"></a>
  <h4 id="TensorFlow_TFShape__ctor_System_Int64___" data-uid="TensorFlow.TFShape.#ctor(System.Int64[])">TFShape(Int64[])</h4>
  <div class="markdown level1 summary"><p>Initializes a new instance of the <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> class.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public TFShape (long[] args);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int64</span>[]</td>
        <td><span class="parametername">args</span></td>
        <td><p>This is a params argument, so you can provide multiple values to it.<br>            A null value means that this is an unknown shape, a single value is used to create a vector,
            two values are used to create a 2-D matrix and so on.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="properties">Properties
  </h3>
  
  
  <a id="TensorFlow_TFShape_IsFullySpecified_" data-uid="TensorFlow.TFShape.IsFullySpecified*"></a>
  <h4 id="TensorFlow_TFShape_IsFullySpecified" data-uid="TensorFlow.TFShape.IsFullySpecified">IsFullySpecified</h4>
  <div class="markdown level1 summary"><p>Gets a value indicating whether all the dimensions in the <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> are fully specified.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public bool IsFullySpecified { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><p><code>true</code> if is fully specified; otherwise, <code>false</code>.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_IsLongArray_" data-uid="TensorFlow.TFShape.IsLongArray*"></a>
  <h4 id="TensorFlow_TFShape_IsLongArray" data-uid="TensorFlow.TFShape.IsLongArray">IsLongArray</h4>
  <div class="markdown level1 summary"><p>Gets a value indicating whether one of the dimensions <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> in the shape is larger than Int32.MaxValue.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public bool IsLongArray { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Boolean</span></td>
        <td><p><code>true</code> if is long array; otherwise, <code>false</code>.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_Item_" data-uid="TensorFlow.TFShape.Item*"></a>
  <h4 id="TensorFlow_TFShape_Item_System_Int32_" data-uid="TensorFlow.TFShape.Item(System.Int32)">Item(Int32)</h4>
  <div class="markdown level1 summary"><p>Gets the dimensions for the specified index.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public long this[int idx] { get; }</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><span class="parametername">idx</span></td>
        <td><p>Index.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int64</span></td>
        <td><p>To be added.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_NumDimensions_" data-uid="TensorFlow.TFShape.NumDimensions*"></a>
  <h4 id="TensorFlow_TFShape_NumDimensions" data-uid="TensorFlow.TFShape.NumDimensions">NumDimensions</h4>
  <div class="markdown level1 summary"><p>Number of dimensions represented by this shape.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public int NumDimensions { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><p>The number dimensions, -1 if the number of dimensions is unknown, 0 if the shape represent a scalar, 1 for a vector, 2 for a matrix and so on..</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_Scalar_" data-uid="TensorFlow.TFShape.Scalar*"></a>
  <h4 id="TensorFlow_TFShape_Scalar" data-uid="TensorFlow.TFShape.Scalar">Scalar</h4>
  <div class="markdown level1 summary"><p>This shape is used to represent scalar values.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public static TensorFlow.TFShape Scalar { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><p>The scalar.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_Unknown_" data-uid="TensorFlow.TFShape.Unknown*"></a>
  <h4 id="TensorFlow_TFShape_Unknown" data-uid="TensorFlow.TFShape.Unknown">Unknown</h4>
  <div class="markdown level1 summary"><p>Represents an unknown number of dimensions in the tensor.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public static TensorFlow.TFShape Unknown { get; }</code></pre>
  </div>
  <h5 class="propertyValue">Property Value</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><p>The unknown.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="methods">Methods
  </h3>
  
  
  <a id="TensorFlow_TFShape_AsTensor_" data-uid="TensorFlow.TFShape.AsTensor*"></a>
  <h4 id="TensorFlow_TFShape_AsTensor" data-uid="TensorFlow.TFShape.AsTensor">AsTensor()</h4>
  <div class="markdown level1 summary"><p>Returns the shape as a 1-dimensional tensor with each element corresponding to the specified shape dimension.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public TensorFlow.TFTensor AsTensor ();</code></pre>
  </div>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFTensor.html">TFTensor</a></td>
        <td><p>The tensor.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_GetLength_" data-uid="TensorFlow.TFShape.GetLength*"></a>
  <h4 id="TensorFlow_TFShape_GetLength_System_Int32_" data-uid="TensorFlow.TFShape.GetLength(System.Int32)">GetLength(Int32)</h4>
  <div class="markdown level1 summary"><p>Gets the length of the specified dimension in the tensor</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public int GetLength (int dimension);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><span class="parametername">dimension</span></td>
        <td><p>Dimension.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span></td>
        <td><p>The length, -1 for shapes that have an unknown dimension.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_ToArray_" data-uid="TensorFlow.TFShape.ToArray*"></a>
  <h4 id="TensorFlow_TFShape_ToArray" data-uid="TensorFlow.TFShape.ToArray">ToArray()</h4>
  <div class="markdown level1 summary"><p>Returns the shape as an array</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public long[] ToArray ();</code></pre>
  </div>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int64</span>[]</td>
        <td><p>null if the shape represents an unknown shape, otherwise an array with N elements, one per dimension, and each element can be either -1 (if the dimension size is unspecified) or the size of the dimension.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_ToIntArray_" data-uid="TensorFlow.TFShape.ToIntArray*"></a>
  <h4 id="TensorFlow_TFShape_ToIntArray" data-uid="TensorFlow.TFShape.ToIntArray">ToIntArray()</h4>
  <div class="markdown level1 summary"><p>Returns the shape as an array</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public int[] ToIntArray ();</code></pre>
  </div>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.Int32</span>[]</td>
        <td><p>null if the shape represents an unknown shape, otherwise an array with N elements, one per dimension, and each element can be either -1 (if the dimension size is unspecified) or the size of the dimension.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_ToString_" data-uid="TensorFlow.TFShape.ToString*"></a>
  <h4 id="TensorFlow_TFShape_ToString" data-uid="TensorFlow.TFShape.ToString">ToString()</h4>
  <div class="markdown level1 summary"><p>Returns a <span class="xref">System.String</span> that represents the current <a class="xref" href="TensorFlow.TFShape.html">TFShape</a>.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public override string ToString ();</code></pre>
  </div>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><span class="xref">System.String</span></td>
        <td><p>A <span class="xref">System.String</span> that represents the current <a class="xref" href="TensorFlow.TFShape.html">TFShape</a>.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h3 id="operators">Operators
  </h3>
  
  
  <a id="TensorFlow_TFShape_op_Addition_" data-uid="TensorFlow.TFShape.op_Addition*"></a>
  <h4 id="TensorFlow_TFShape_op_Addition_TensorFlow_TFShape_TensorFlow_TFShape_" data-uid="TensorFlow.TFShape.op_Addition(TensorFlow.TFShape,TensorFlow.TFShape)">op_Addition(TFShape, TFShape)</h4>
  <div class="markdown level1 summary"><p>Adds a <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> to a <a class="xref" href="TensorFlow.TFShape.html">TFShape</a>, yielding a shape made up of the concatenation of the first and the second shapes.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public static TensorFlow.TFShape op_Addition (TensorFlow.TFShape left, TensorFlow.TFShape right);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><span class="parametername">left</span></td>
        <td><p>The first <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> to add.</p>
</td>
      </tr>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><span class="parametername">right</span></td>
        <td><p>The second <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> to add.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><p>The <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> that is the sum of the values of <code>left</code> and <code>right</code>.</p>
</td>
      </tr>
    </tbody>
  </table>
  
  
  <a id="TensorFlow_TFShape_op_Implicit_" data-uid="TensorFlow.TFShape.op_Implicit*"></a>
  <h4 id="TensorFlow_TFShape_op_Implicit_TensorFlow_TFShape_to_TensorFlow_TFTensor_" data-uid="TensorFlow.TFShape.op_Implicit(TensorFlow.TFShape to TensorFlow.TFTensor)">op_Implicit(TFShape to TFTensor)</h4>
  <div class="markdown level1 summary"><p>Performs an implicit conversion from <a class="xref" href="TensorFlow.TFShape.html">TFShape</a> to <a class="xref" href="TensorFlow.TFTensor.html">TFTensor</a>.</p>
</div>
  <div class="markdown level1 conceptual"></div>
  <h5 class="decalaration">Declaration</h5>
  <div class="codewrapper">
    <pre><code class="lang-csharp hljs">public static TensorFlow.TFTensor op_Implicit (TensorFlow.TFShape shape);</code></pre>
  </div>
  <h5 class="parameters">Parameters</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Name</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFShape.html">TFShape</a></td>
        <td><span class="parametername">shape</span></td>
        <td><p>The shape.</p>
</td>
      </tr>
    </tbody>
  </table>
  <h5 class="returns">Returns</h5>
  <table class="table table-bordered table-striped table-condensed">
    <thead>
      <tr>
        <th>Type</th>
        <th>Description</th>
      </tr>
    </thead>
    <tbody>
      <tr>
        <td><a class="xref" href="TensorFlow.TFTensor.html">TFTensor</a></td>
        <td><p>The result of the conversion.</p>
</td>
      </tr>
    </tbody>
  </table>
</article>
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